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Mendeley readers
Chapter title |
Coarse-to-Fine Auto-Encoder Networks (CFAN) for Real-Time Face Alignment
|
---|---|
Chapter number | 1 |
Book title |
Computer Vision – ECCV 2014
|
Published by |
Springer, Cham, September 2014
|
DOI | 10.1007/978-3-319-10605-2_1 |
Book ISBNs |
978-3-31-910604-5, 978-3-31-910605-2
|
Authors |
Jie Zhang, Shiguang Shan, Meina Kan, Xilin Chen, Zhang, Jie, Shan, Shiguang, Kan, Meina, Chen, Xilin |
Mendeley readers
The data shown below were compiled from readership statistics for 200 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
China | 2 | 1% |
United Kingdom | 1 | <1% |
France | 1 | <1% |
Japan | 1 | <1% |
United States | 1 | <1% |
Unknown | 194 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 53 | 27% |
Student > Master | 50 | 25% |
Researcher | 16 | 8% |
Student > Bachelor | 14 | 7% |
Student > Postgraduate | 6 | 3% |
Other | 18 | 9% |
Unknown | 43 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 111 | 56% |
Engineering | 29 | 14% |
Mathematics | 3 | 2% |
Neuroscience | 2 | 1% |
Agricultural and Biological Sciences | 1 | <1% |
Other | 5 | 3% |
Unknown | 49 | 25% |